Triple
T17901106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nishinari-ku |
E447579
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Airin district
Airin district is a poverty-stricken area in Osaka’s Nishinari Ward known for its large day-laborer population, cheap lodging houses, and visible homelessness.
|
E1295653
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Airin district | Statement: [Nishinari-ku, contains, Airin district]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Airin district Context triple: [Nishinari-ku, contains, Airin district]
-
A.
Duji District
Duji District is an administrative urban district of Huaibei City in Anhui Province, eastern China.
-
B.
Hanang District
Hanang District is an administrative district in northern Tanzania known for its agricultural communities and the prominent Mount Hanang.
-
C.
Buka District
Buka District is an administrative district located within the Tashkent Region of Uzbekistan.
-
D.
Truk District
Truk District was a former administrative district of the Trust Territory of the Pacific Islands centered on the Truk (now Chuuk) Lagoon in Micronesia.
-
E.
Tanah Merah District
Tanah Merah District is an administrative district in Kelantan, Malaysia, known for its predominantly rural communities and agricultural-based economy.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Airin district Triple: [Nishinari-ku, contains, Airin district]
Generated description
Airin district is a poverty-stricken area in Osaka’s Nishinari Ward known for its large day-laborer population, cheap lodging houses, and visible homelessness.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Airin district Target entity description: Airin district is a poverty-stricken area in Osaka’s Nishinari Ward known for its large day-laborer population, cheap lodging houses, and visible homelessness.
-
A.
Duji District
Duji District is an administrative urban district of Huaibei City in Anhui Province, eastern China.
-
B.
Hanang District
Hanang District is an administrative district in northern Tanzania known for its agricultural communities and the prominent Mount Hanang.
-
C.
Buka District
Buka District is an administrative district located within the Tashkent Region of Uzbekistan.
-
D.
Truk District
Truk District was a former administrative district of the Trust Territory of the Pacific Islands centered on the Truk (now Chuuk) Lagoon in Micronesia.
-
E.
Tanah Merah District
Tanah Merah District is an administrative district in Kelantan, Malaysia, known for its predominantly rural communities and agricultural-based economy.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8b9f59bd48190a6fc925a855b8bac |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49e98fb688190815ac308e5ed7fde |
completed | April 19, 2026, 9:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a031b286b088190b6cf9731da839669 |
completed | May 12, 2026, 12:20 p.m. |
| NEDg | Description generation | batch_6a031c3658988190b59fa17d616cad9b |
completed | May 12, 2026, 12:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a031c9914dc819099da3b2174a5fbc7 |
completed | May 12, 2026, 12:27 p.m. |
Created at: April 10, 2026, 10:19 a.m.